The Atypicality of Verb-Final Clauses in Japanese Conversation: Toward a Speaker-Centered Characterization of Japanese Clausal Syntax
Bibliographic record
Abstract
The so-called canonical clause, consisting of case-marked NPs and a final finite verb, has played a central role in discussions of Japanese for the past several decades. The current study explores the nature of such clauses in everyday Japanese conversation. Everyday conversation is considered the most fundamental form of language, and large-scale corpora of Japanese everyday conversation have only become available in recent years, enabling projects like ours. One key finding is that clauses ending with a finite verb are rare, challenging the centrality of the canonical clause in Japanese grammar. Instead, we observe that the verb is usually followed by additional elements that convey pragmatic information. This observation suggests that the canonical clause for Japanese speakers should also include these pragmatic elements. We have observed further that the relatively uncommon examples that do end with a finite verb often involve five frequent semantically light verbs. A preliminary study of one of these verbs, chigau ‘to differ’, reveals that, typically without overt NPs, it functions more like a particle than the verb of a clause. This further calls into question the idea that the canonical clause in Japanese ends with a finite verb.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".